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SUMMARY:Machine learning to determine the fitting parameters of ferroelect
 ric-dielectric nanocomposites dielectric response
DTSTART;VALUE=DATE-TIME:20260922T134500Z
DTEND;VALUE=DATE-TIME:20260922T135000Z
DTSTAMP;VALUE=DATE-TIME:20260914T013420Z
UID:indico-contribution-557@indico.bitp.kiev.ua
DESCRIPTION:Speakers: Oleksii Bereznykov (Institute of Physics\, NAS of Uk
 raine)\nOne of the problems of analyzing experimental electrophysical depe
 ndences is determining the parameters of the theoretical model that best r
 eproduces the form of measured dielectric response of ferroelectric-dielec
 tric nanocomposites. For complex nonlinear models\, such a problem may hav
 e several close solutions\, be sensitive to the initial approximation\, an
 d require significant computational costs. We investigated the possibility
  of using machine learning for automated determination of the parameters o
 f a physical model intended for forming an experimental state of the ferro
 electric-dielectric nanocomposites. The study of ferroelectric-dielectric 
 nanocomposites was conducted based on the Effective Medium Approximation (
 EMA) [1] and Heywang models [2]. For each model\, a set of curves was form
 ed when varying its physical parameters in given regions. Thus\, each curv
 e corresponds to a known set of parameters\, which allowed us to form a tr
 aining sample for the regression problem.\nTypically\, EMA considers a qua
 dratic equation for the effective permittivity of a binary mixture:\n$(1-
 μ)  \\frac{(ε_{eff}^*-ε_{b}^*)}{(1-n_a ) ε_{eff}^*+n_a  ε_b^*}+μ \\f
 rac{(ε_{eff}^*-ε_a^*)}{(1-n_a ) ε_{eff}^*+n_a  ε_a^*}=0$              
          (1)\nhere $ε_a^*\, ε_b^*$ are the relative complex permittiviti
 es of components "a" and "b" respectively\, $μ$ and $1-μ$ are the relati
 ve volume fractions of components "a" and "b" respectively\, and $n_a$ is 
 the depolarization field factor for the inclusion of type "a".\nFollowing 
 Heywang model\, the expected Arrhenius-type and/or the Mott-type temperatu
 re dependences (as well as a general stretched-exponential law) for the ef
 fective conductivity of the nanopowders could be modified by introduction 
 of the effective dielectric permittivity. Thus\, we use the following fitt
 ing function for effective conductivity:\n$σ_eff (T\,ω)=σ_A^0 (ω)exp[-
 (\\frac{E_A}{(k_B Tε_{eff}(T))}^λ ]$.                (2)\nHere $E_A$ is 
 an activation energy of the space charges in the cores/shells (A = C or S)
 . The positive fitting parameter $λ$ varies in the range $0\n\nhttps://in
 dico.bitp.kiev.ua/event/18/contributions/557/
LOCATION:Bogolyubov Institute for Theoretical Physics Conference Hall
URL:https://indico.bitp.kiev.ua/event/18/contributions/557/
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